19,997 machine learning datasets
19,997 dataset results
The MICCAI 2020 EMIDEC dataset is a dataset for classifying normal and pathological cases from the clinical information with or without DE-MRI, and secondly to automatically detect the different relevant areas (the myocardial contours, the infarcted area and the permanent microvascular obstruction area (no-reflow area)) from a series of short-axis DE-MRI covering the left ventricle. The segmentation allows one to make a quantification of the MI, in absolute value (mm3) or percentage of the myocardium.
This is a Dataset for Arabic/English text detection and optical character recognition. All image data are text-slides extracted from PowerPoint files downloaded from Internet through the Google API. All annotations are automatically generated mainly through the WinCom32 Python API. Postprocess is also applied to place a more accurate text bounding box or to suppress false-alarms, e.g. a text box only containing spaces. Finally, all annotation results are briefly reviewed by human to reject extreme bad samples, e.g. a slide with a large portion of copied table as image. In summary, this dataset contains 10,692 images, and roughly 100K line samples.
German affixoids are a type of morpheme in between affixes and free stems.
The Persian Consonant Vowel Combination (PCVC) dataset is a phoneme based speech dataset, and also the first free Persian speech dataset to help Persian speech researchers. This dataset contains of 23 Persian consonants and 6 vowels. The sound samples are all possible combinations of vowels and consonants (138 samples for each speaker) with a length of 30000 data samples. The sample rate of all speech samples is 48000 which means there are 48000 sound samples in every 1 second. In each sample, sound starts with consonant and then there is a vowel sound and at last there is silent. length of silence is dependent on length of combination of consonant and vowel. For example if combination ends in 20000th data sample, so the rest of 10000 sample (until 30000, the length of each sound sample) are silence.
The Arabic Speech Corpus (1.5 GB) is a Modern Standard Arabic (MSA) speech corpus for speech synthesis. The corpus contains phonetic and orthographic transcriptions of more than 3.7 hours of MSA speech aligned with recorded speech on the phoneme level. The annotations include word stress marks on the individual phonemes The Speech corpus has been developed as part of PhD work carried out by Nawar Halabi at the University of Southampton. The corpus was recorded in south Levantine Arabic (Damascian accent) using a professional studio. Synthesized speech as an output using this corpus has produced a high quality, natural voice.
The MIVIA audio events data set is composed of a total of 6000 events for surveillance applications, namely glass breaking, gun shots and screams. The 6000 events are divided into a training set (composed of 4200 events) and a test set (composed of 1800 events).
The Princeton Shape dataset provides a repository of 3D models and software tools for evaluating shape-based retrieval and analysis algorithms. The motivation is to promote the use of standardized data sets and evaluation methods for research in matching, classification, clustering, and recognition of 3D models. Researchers are encouraged to use these resources to produce comparisons of competing algorithms in future publications. There are 1,814 models in total.
IKEA 3D is a dataset of IKEA 3D models and aligned images, which is suitable for pose estimation. There are 759 images and 219 models including Sketchup (skp) and Wavefront (obj) files.
The Daimler Urban Segmentation Dataset is a dataset for semantic segmentation. It consists of video sequences recorded in urban traffic. The dataset consists of 5000 rectified stereo image pairs with a resolution of 1024x440. 500 frames (every 10th frame of the sequence) come with pixel-level semantic class annotations into 5 classes: ground, building, vehicle, pedestrian, sky. Dense disparity maps are provided as a reference, however these are not manually annotated but computed using semi-global matching (sgm).
The Interestingness dataset contains movie excerpts and key-frames and corresponding ground truth files based on classification into interesting and non-interesting samples. It is used for multimedia content interestingness classification. The dataset is composed of:
LASIESTA (Labeled and Annotated Sequences for Integral Evaluation of SegmenTation Algorithms) is a segmentation and detection dataset composed by many real indoor and outdoor sequences organized into categories, each of one covering a specific challenge in moving object detection strategies.
The PIROPO database (People in Indoor ROoms with Perspective and Omnidirectional cameras) comprises multiple sequences recorded in two different indoor rooms, using both omnidirectional and perspective cameras. The sequences contain people in a variety of situations, including people walking, standing, and sitting. Both annotated and non-annotated sequences are provided, where ground truth is point-based (each person in the scene is represented by the point located in the center of its head). In total, more than 100,000 annotated frames are available.
The Edge Milling Heads data set comprises 144 images of an edge profile cutting head of a milling machine. The head tool contains a total of 30 cutting inserts. The cutting head is formed by 6 diagonals of inserts in radial direction along the tool perimeter, encompassing 5 inserts per diagonal in axial direction. Positions of the last and first inserts of consecutive diagonals are aligned in the same vertical. Therefore, even though there are 30 inserts in total, there are 24 equally spaced positions of inserts along the tool perimeter. Additionally, inserts are squared shape with four 90º indexable cutting edges. Inserts are fastened with a screw. Rake angle is 0.
The VXC TSG is based on samples taken from the ceramic tile industry and is comprised of 14 ceramic tile models, 42 surface grades and 960 pieces. It has been built in the VxC laboratory, at the Polytechnic University of Valencia, in collaboration with Keraben S.A., a large ceramic tile company located at Nules province of Castellón (Spain).
The Panoramic Image Database is a panoramic image dataset. The databases were collected by Andrew Vardy while visiting with the Computer Engineering group in February and March of 2004. Images were captured by a robot-mounted camera, pointed upwards at a hyperbolic mirror. The camera was an ImagingSource DFK 4303. The robot was an ActivMedia Pioneer 3-DX. The mirror was a large wide-view hyperbolic mirror from Accowle Ltd. The hyperbolic mirror expands the camera's field of view to allow the capture of panoramic images.
OCTCBVS is a benchmark dataset for testing and evaluating novel and state-of-the-art computer vision algorithms. The benchmark contains videos and images recorded in and beyond the visible spectrum and is available for free to all researchers in the international computer vision communities.
The DogCentric Activity dataset is composed of dog activity videos taken from a first-person animal viewpoint. The dataset contains 10 different types of activities, including activities performed by the dog himself/herself, interactions between people and the dog, and activities performed by people or cars.
The CMU Wilderness Multilingual Speech Dataset is a dataset of over 700 different languages providing audio, aligned text and word pronunciations. On average each language provides around 20 hours of sentence-lengthed transcriptions.
CUHK Square data set is for transfer learning research on adapting generic pedestrian detectors. It includes a traffic video sequence of 60 minutes long. It is recorded by a stationary camera. The size of the scene is 720 by 576.
CUHK occlusion dataset includes 1,063 images with occluded pedestrians. It is used for Human Detection with occlusion handling in crowded scenes.